Matthew Coudron

We give a comprehensive characterization of the computational power of shallow quantum circuits combined with classical computation. Specifically, we show that the following statements hold relative to a random oracle: (a) latex mathsfBPP^QNC^BPP neq mathsfBQP. This refutes Jozsa's conjecture [Joz05] in the random oracle model. As a result, this gives the first instantiatable separation between the classes by replacing the oracle with a cryptographic hash function, yielding a resolution to one of Aaronson's ten semi-grand challenges in quantum computing. (b) latex mathsfQNC^BPP notsubseteq mathsfBPP^QNC and latex mathsfBPP^QNC notsubseteq mathsfQNC^BPP This shows that there is a subtle interplay between classical computation and shallow quantum computation. In fact, for the second separation, we establish that, for some problems, the ability to perform adaptive measurements in a single shallow quantum circuit, is more useful than the ability to perform polynomially many shallow quantum circuits without adaptive measurements. (c) There exists a 2-message proof of quantum depth protocol. Such a protocol allows a classical verifier to efficiently certify that a prover must be performing a computation of some minimum quantum depth. Our proof of quantum depth can be instantiated using the recent proof of quantumness construction by Yamakawa and Zhandry [YZ22]. [Joz05] - Richard Jozsa. ""An introduction to measurement based quantum computation."" In: Quantum Information Processing 199 (Sept. 2005). [YZ22] - Takashi Yamakawa and Mark Zhandry. ""Verifiable quantum advantage without structure."" In: 63rd Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2022.

The so-called welded tree problem provides an example of a black-box problem that can be solved exponentially faster by a quantum walk than by any classical algorithm. Given the name of a special ENTRANCE vertex, a quantum walk can find another distinguished EXIT vertex using polynomially many queries, though without finding any particular path from ENTRANCE to EXIT. It has been an open problem for twenty years whether there is an efficient quantum algorithm for finding such a path, or if the path-finding problem is hard even for quantum computers. We show that a natural class of efficient quantum algorithms provably cannot find a path from ENTRANCE to EXIT. Specifically, we consider algorithms that, within each branch of their superposition, always store a set of vertex labels that form a connected subgraph including the ENTRANCE, and that only provide these vertex labels as inputs to the oracle. While this does not rule out the possibility of a quantum algorithm that efficiently finds a path, it is unclear how an algorithm could benefit by deviating from this behavior. Our no-go result suggests that, for some problems, quantum algorithms must necessarily forget the path they take to reach a solution in order to outperform classical computation.

Abstract We present a classical algorithm that, for any geometrically-local, constant-depth quantum circuit $C$, and any bit string $x \in \{0,1\}^n$, can compute the quantity $|\bra{0^{\otimes n}}C \ket{x}|^2$ to within any inverse-polynomial additive error in quasi-polynomial time. It is known that it is $\#P$-hard to compute this same quantity to within $2^{-n^2}$ additive error \cite{Mov19}. The previous best known algorithm for this problem used $O(2^{n^{1/3}}\poly(1/\epsilon))$ time to compute probabilities to within additive error $\epsilon$ \cite{BGM19}. Notably, the \cite{BGM19} paper included an elegant polynomial time algorithm for the same estimation task with 2D circuits, which makes a novel use of 1D Matrix Product States carefully tailored to the 2D geometry of the circuit in question. Surprisingly, it is not clear that it is possible to extend this use of MPS to address the case of 3D circuits in polynomial time. This raises a natural question as to whether the computational complexity of the 3D problem might be drastically higher than that of the 2D problem. In this work we address this question by exhibiting a quasi-polynomial time algorithm for the 3D case. In order to surpass the technical barriers encountered by previously known techniques we are forced to pursue a novel approach: Constructing a recursive sub-division of the given 3D circuit using carefully designed block-encodings.